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Null hypothesis significance testing: a short tutorial

Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of...

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Detalles Bibliográficos
Autor principal: Pernet, Cyril
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635437/
https://www.ncbi.nlm.nih.gov/pubmed/29067159
http://dx.doi.org/10.12688/f1000research.6963.3
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author Pernet, Cyril
author_facet Pernet, Cyril
author_sort Pernet, Cyril
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description Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of significance (Fisher) and test of acceptance (Newman-Pearson) and point to common interpretation errors regarding the p-value. I then present the related concepts of confidence intervals and again point to common interpretation errors. Finally, I discuss what should be reported in which context. The goal is to clarify concepts to avoid interpretation errors and propose reporting practices.
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spelling pubmed-56354372017-10-23 Null hypothesis significance testing: a short tutorial Pernet, Cyril F1000Res Opinion Article Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of significance (Fisher) and test of acceptance (Newman-Pearson) and point to common interpretation errors regarding the p-value. I then present the related concepts of confidence intervals and again point to common interpretation errors. Finally, I discuss what should be reported in which context. The goal is to clarify concepts to avoid interpretation errors and propose reporting practices. F1000Research 2016-10-10 /pmc/articles/PMC5635437/ /pubmed/29067159 http://dx.doi.org/10.12688/f1000research.6963.3 Text en Copyright: © 2016 Pernet C http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Opinion Article
Pernet, Cyril
Null hypothesis significance testing: a short tutorial
title Null hypothesis significance testing: a short tutorial
title_full Null hypothesis significance testing: a short tutorial
title_fullStr Null hypothesis significance testing: a short tutorial
title_full_unstemmed Null hypothesis significance testing: a short tutorial
title_short Null hypothesis significance testing: a short tutorial
title_sort null hypothesis significance testing: a short tutorial
topic Opinion Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635437/
https://www.ncbi.nlm.nih.gov/pubmed/29067159
http://dx.doi.org/10.12688/f1000research.6963.3
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